Wireless assisted GPS systems with emerging E911 compliance standards require reduced acquisition time in GPS receivers. The user's location information needs to be accurately communicated in the shortest possible time to emergency support providers. If the location data is not accurate, the emergency dispatchers may experience difficulty in routing 911 calls to the appropriate center. Mobile phones also need to be operable indoors and in urban canyons. Today's GPS systems also need to have the capability to handle weak signals and respond with both speed and location accuracy. For example, E911 compliance requires that the object be identified within 125 meters and within a 5 second span in most instances.
The conventional method to determine time to first fix (TTFF) is through the use of multiple hardware blocks. TTFF performance is dependent on the correlation acquisition process. For example, incoming GPS signals from twelve respective satellites are channeled to twelve hardware blocks partitioned in the correlator. The twelve hardware blocks then perform the correlation exercise in parallel. The above conventional approach faces significant challenges. The use of twelve hardware blocks increases the gate count of the device. This in turn increases the size of the correlator device and hence the overall real estate of the GPS receiver. There is a strong industry move towards GPS integration in automotive and handheld applications. These applications demand a small form factor GPS receiver. However, if an attempt is made to design a higher gate count device in a smaller form factor hardware block, the cost and complexity of the design increases.
In the frequency domain correlation approach, there is a trade-off between the ability to detect weak signals and to improve acquisition time. The strength of the signal determines the necessary length and period of the signal that needs to be analyzed. For weak signals, the data length required for analysis increases. However, when the length of data increases, the frequency of the correlation operation decreases. This in turn increases the acquisition time of the signal.
Hence, it is not possible to overcome the aforementioned tradeoff between signal strength, acquisition time and gate count if the conventional time domain or frequency domain approach and conventional sampling method is used. The correlation analysis is performed either in the time domain through convolution, or in the frequency domain through Fourier transform. The correlation operation is performed repeatedly in fixed periods for every new incoming data point. This invention optimizes this sampling procedure to allow a longer data input string to be taken with multiple data points and by allowing the sampling operations to be performed simultaneously on multiple data points in the data string. “Correlation” between two series implies the multiplication of the elements of one series with the elements of the other, the result being a single value. “Convolution” between two series implies creating a third series by filtering the second series using a filter, corresponding to that of the first series.
Consider two signals, one received from a satellite and the other from a locally generated reference signal. A “correlation” between the two signals is a measurement of similarity between the signals obtained by multiplying the two sequences together and summing the result in an accumulator. The incoming signals are decomposed into in-phase and quadrature components prior to the correlation process. If correlation takes place for “n” samples of a given signal, the “n+1” samples of two signals can be multiplied and added to the previous result of the correlation of “n” samples. This repetitive process is referred to as “updating” of the correlation. This updating process continues until a final result is obtained to compare with a threshold or for further processing. Next, the correlation process starts for a new set of values. This process of integrating the product of samples of two signals for a finite duration is termed as “integrate and dump”.
In most applications, the relative phasing between an incoming data sequence and a locally generated sequence needs to be determined. A series of correlation operations are performed between the incoming signal and a set of shifted versions of locally generated code signal. A particular relative phasing between two sequences is termed a “lag”, where this term comes from its relation to delay. The correlation operation consists of shifting to the right by 1 for each lag, point wise multiplying and finally summing the results.
Hardware correlators are used in GPS receivers to perform the correlation process. The correlator is connected between a Radio Frequency Down Converter and a base band processor. The base band processor can be either an Advance Risk Machine (ARM) processor or a Digital Signal Processor (DSP).
The architecture of the correlator determines the TTFF performance of the receivers. Typically, conventional receivers with a very low gate count of approximately 150K gates to 200K gates achieve TTFF of approximately 70 seconds to 80 seconds under normal signal conditions. As discussed above, this is not sufficient to meet the requirements of the new applications in the market. Other architectures overcome this problem using Fast Fourier Transform (FFT) based correlators. But the gate count of these correlators is of the order of 400K gates and above.
Typically, multitap correlation in a parallel processing scheme increases correlator hardware complexity. For example, for a 10-chip multitap, each chip requires 4 accumulators. A total of 40 accumulators would therefore be required per channel. But with 12 channels using the multitap in parallel, there is a need for 480 accumulators. The large number of accumulators increases the gate count of the GPS receiver. This invention uses a sequential multitap correlation process that significantly reduces the number of accumulators and hence reduces the overall gate count.
The integration time of a GPS receiver determines the maximum frequency range that can be searched. For example, for an integration time of one millisecond, the maximum frequency that can be detected is 500 Hz. This invention increases the frequency range of the signals that can be searched by decreasing the integration time.
There are different stages to a GPS reception. In a cold start, the GPS correlator does not have a prior estimate of the frequency shifts of the incoming signals. Whereas, in the case of a warm start, the GPS receiver already has an estimate of the Doppler frequency. Typically, a correlator has a cold start of 75 seconds, a warm start of 45 seconds and a hot start of 10 seconds. There is a market need to reduce these start periods in new market applications.
The GPS receivers use RF down converters that possess a reference clock. If there is a shift in reference clock, there will be a corresponding shift in the frequency detected for the incoming signal. A sub-optimal oscillator with an inherent clock frequency shift causes problems for warm starts. In a warm start, it is difficult to determine the incoming signal's carrier frequency and the frequencies must be searched for a wider range of frequencies.
Customers today require a low gate count GPS receiver with a reduced time for first fix. To achieve this, the number of accumulators used in the GPS receiver must be reduced. The ability to detect weak signals in a reduced time for first fix is also a strong market need.